Adaptive, personalized closed-loop therapy for Parkinson’s disease: biochemical, neurophysiological, and wearable sensing systems

Biase, Lazzaro di; Tinkhauser, Gerd; Moraud, Eduardo Martin; Caminiti, Maria Letizia; Pecoraro, Pasquale Maria

doi:10.1080/14737175.2021.2000392

Cited by 20 publications

(19 citation statements)

References 199 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the future, some of these challenges could be addressed by pairing additional external devices wirelessly with the DBS implants to support physiological and behavioral tracking and increase the precision of the patienttailored control strategies. 1,88 In the long term for chronic treatment, an all-in-one implanted system is preferable over putting additional hardware burden to the patient. With this article we hope to inspire the discussion in the community to address strategies for handling the growing degrees of freedom of the parameter space required to calibrate adaptive stimulation according to heterogeneous symptom profiles.…”

Section: Technical Challenges For Brain Activity Recordings During St...mentioning

confidence: 99%

Adaptive Deep Brain Stimulation: From Experimental Evidence Toward Practical Implementation

Neumann

Gilron²,

Little

et al. 2023

Movement Disorders

Self Cite

View full text Add to dashboard Cite

A BS TRACT: Closed-loop adaptive deep brain stimulation (aDBS) can deliver individualized therapy at an unprecedented temporal precision for neurological disorders. This has the potential to lead to a breakthrough in neurotechnology, but the translation to clinical practice remains a significant challenge. Via bidirectional implantable brain-computer-interfaces that have become commercially available, aDBS can now sense and selectively modulate pathophysiological brain circuit activity. Pilot studies investigating different aDBS control strategies showed promising results, but the short experimental study designs have not yet supported individualized analyses of patientspecific factors in biomarker and therapeutic response dynamics. Notwithstanding the clear theoretical advantages of a patient-tailored approach, these new stimulation possibilities open a vast and mostly unexplored parameter space, leading to practical hurdles in the implementation and development of clinical trials. Therefore, a thorough understanding of the neurophysiological and neurotechnological aspects related to aDBS is crucial to develop evidence-based treatment regimens for clinical practice. Therapeutic success of aDBS will depend on the integrated development of strategies for feedback signal identification, artifact mitigation, signal processing, and control policy adjustment, for precise stimulation delivery tailored to individual patients. The present review introduces the reader to the neurophysiological foundation of aDBS for Parkinson's disease (PD) and other network disorders, explains currently available aDBS control policies, and highlights practical pitfalls and difficulties to be addressed in the upcoming years. Finally, it highlights the importance of interdisciplinary clinical neurotechnological research within and across DBS centers, toward an individualized patient-centered approach to invasive brain stimulation.

show abstract

Section: Technical Challenges For Brain Activity Recordings During St...mentioning

confidence: 99%

Adaptive Deep Brain Stimulation: From Experimental Evidence Toward Practical Implementation

Neumann

Gilron²,

Little

et al. 2023

Movement Disorders

Self Cite

View full text Add to dashboard Cite

show abstract

“…77,78 For these scenarios, a spectral topographic map may still be informative as a reference atlas tool to inform multicontact DBS programming, alone or in conjunction with imaging, modeling, or wearable tools. 4,6,32,79,80…”

Section: Toward Automatization Of Dbs Programmingmentioning

confidence: 99%

Spectral Topography of the Subthalamic Nucleus to Inform Next‐Generation Deep Brain Stimulation

et al. 2023

Self Cite

View full text Add to dashboard Cite

Background The landscape of neurophysiological symptoms and behavioral biomarkers in basal ganglia signals for movement disorders is expanding. The clinical translation of sensing‐based deep brain stimulation (DBS) also requires a thorough understanding of the anatomical organization of spectral biomarkers within the subthalamic nucleus (STN). Objectives The aims were to systematically investigate the spectral topography, including a wide range of sub‐bands in STN local field potentials (LFP) of Parkinson's disease (PD) patients, and to evaluate its predictive performance for clinical response to DBS. Methods STN‐LFPs were recorded from 70 PD patients (130 hemispheres) awake and at rest using multicontact DBS electrodes. A comprehensive spatial characterization, including hot spot localization and focality estimation, was performed for multiple sub‐bands (delta, theta, alpha, low‐beta, high‐beta, low‐gamma, high‐gamma, and fast‐gamma (FG) as well as low‐ and fast high‐frequency oscillations [HFO]) and compared to the clinical hot spot for rigidity response to DBS. A spectral biomarker map was established and used to predict the clinical response to DBS. Results The STN shows a heterogeneous topographic distribution of different spectral biomarkers, with the strongest segregation in the inferior‐superior axis. Relative to the superiorly localized beta hot spot, HFOs (FG, slow HFO) were localized up to 2 mm more inferiorly. Beta oscillations are spatially more spread compared to other sub‐bands. Both the spatial proximity of contacts to the beta hot spot and the distance to higher‐frequency hot spots were predictive for the best rigidity response to DBS. Conclusions The spatial segregation and properties of spectral biomarkers within the DBS target structure can additionally be informative for the implementation of next‐generation sensing‐based DBS. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

show abstract

“…Several authors suggested that these abnormalities could be used as biomarkers to deliver electrical DBS only in response to pathological neuronal oscillation (adaptative DBS-aDBS). This technique was mainly evaluated in Parkinson’s disease patients [ 57 , 58 , 59 ] in which LFP monitoring could be supported by multiparametric [ 60 ] motor symptoms monitoring [ 61 , 62 , 63 ] with the assistance of artificial intelligence algorithms [ 64 ]. It has been suggested that this protocol could be translated to dystonic patients with specific biomarkers, such as GPi LFPs theta-alpha band activity [ 41 , 42 , 53 ], in combination with dystonic muscle activity monitoring through subcutaneous EMG or wearable accelerometer devices [ 53 ].…”

Section: Clinical Neurophysiologymentioning

confidence: 99%

Dystonia Diagnosis: Clinical Neurophysiology and Genetics

Biase

Santo

Caminiti

et al. 2022

JCM

Self Cite

View full text Add to dashboard Cite

Dystonia diagnosis is based on clinical examination performed by a neurologist with expertise in movement disorders. Clues that indicate the diagnosis of a movement disorder such as dystonia are dystonic movements, dystonic postures, and three additional physical signs (mirror dystonia, overflow dystonia, and geste antagonists/sensory tricks). Despite advances in research, there is no diagnostic test with a high level of accuracy for the dystonia diagnosis. Clinical neurophysiology and genetics might support the clinician in the diagnostic process. Neurophysiology played a role in untangling dystonia pathophysiology, demonstrating characteristic reduction in inhibition of central motor circuits and alterations in the somatosensory system. The neurophysiologic measure with the greatest evidence in identifying patients affected by dystonia is the somatosensory temporal discrimination threshold (STDT). Other parameters need further confirmations and more solid evidence to be considered as support for the dystonia diagnosis. Genetic testing should be guided by characteristics such as age at onset, body distribution, associated features, and coexistence of other movement disorders (parkinsonism, myoclonus, and other hyperkinesia). The aim of the present review is to summarize the state of the art regarding dystonia diagnosis focusing on the role of neurophysiology and genetic testing.

show abstract

Adaptive, personalized closed-loop therapy for Parkinson’s disease: biochemical, neurophysiological, and wearable sensing systems

Cited by 20 publications

References 199 publications

Adaptive Deep Brain Stimulation: From Experimental Evidence Toward Practical Implementation

Adaptive Deep Brain Stimulation: From Experimental Evidence Toward Practical Implementation

Spectral Topography of the Subthalamic Nucleus to Inform Next‐Generation Deep Brain Stimulation

Dystonia Diagnosis: Clinical Neurophysiology and Genetics

Contact Info

Product

Resources

About